Thanks to characteristics such as high beam qualities and high average powers, largely founded on the outstanding characteristics of fibers as an active medium, fiber lasers have become one of the most popular laser technologies. Although most of the advantages of fiber lasers stem from their geometry, the same geometry is the main source of the limitations. In this study, we focused on managing the thermal load by variable absorption coefficient in order to increase the thermal limits, which are an important limitation of further development in fiber technology. Metaheuristic optimization approaches can be used to improve the performance of fiber technologies with physical constraints. The main aim of metaheuristic optimization is to improve the output of the function with respect to the parameters considered as significant. Swarm Optimization approach is one of the powerful metaheuristic approaches proven to be quite promising to address the above issues. In this study, the optimization of the thermal management of the ${\mathit{Er}}^{3+}$-doped ZBLAN fiber laser is performed using Artificial Bee Colony Algorithm (ABC). Additionally, this paper proposes four new strategies of initial parameter setting, repair parameter values, and fitness function for the thermal load of the ${\mathit{Er}}^{3+}$-doped ZBLAN fiber laser with respect to the output power. The results show that the absorption coefficient functions obtained by ABC algorithm give more effective and efficient results than the obtained rising functions.

由于具有高光束质量和高平均功率等特性，而这些特性很大程度上建立在光纤作为活性介质的出色特性基础上，因此光纤激光器已成为最受欢迎的激光技术之一。尽管光纤激光器的大多数优点都来自其几何形状，但是相同的几何形状是限制的主要来源。在这项研究中，我们集中于通过可变吸收系数来管理热负荷，以增加热极限，这是纤维技术进一步发展的重要限制。元启发式优化方法可用于提高具有物理约束的光纤技术的性能。元启发式优化的主要目的是针对被认为重要的参数提高函数的输出。群优化方法是强大的元启发式方法之一，事实证明，该方法很有可能解决上述问题。在这项研究中，对热管理的优化${\mathit{尔}}^{3+}$使用人工蜂群算法（ABC）进行掺杂的ZBLAN光纤激光器。此外，本文提出了四种新的初始参数设置，修复参数值和适应度函数来适应热负荷。${\mathit{尔}}^{3+}$掺杂的ZBLAN光纤激光器的输出功率。结果表明，通过ABC算法获得的吸收系数函数比获得的上升函数提供了更有效的结果。